Machine Learning Engineer jobs in Tel Aviv-Yafo

Description About Tenzai Tenzai is building autonomous AI hackers that think like the world's best offensive security experts, act like them, and then help fix what they find before the real ones do. If this mission speaks to you, come defend the world's software: autonomously, continuously, and in-depth. About the role This is a rare opportunity to work at the intersection of offensive security and AI — and to have your expertise shape a platform used at enterprise scale. Your work will be deployed and used to hack into applications and systems in the real world. Responsibilites • Design and implement reinforcement learning workflows to train state- of- the- art LLMs specializing in cybersecurity. Design tasks, datasets, and benchmarks for training and evaluating LLMs and agents. • Work on experimentation and evaluation systems — evals are key to everything we do. In this role, you will build evaluation pipelines, design and build experiments, and construct simulations. Requirements • Strong understanding of modern LLMs, including training, post-training, RL, fine-tuning, and inference, with hands-on experience deploying LLM-based systems in production. • Hands-on experience building an agent, including working with complex loops, context engineering, and long-execution tooling. • 5+ years of hands-on programming experience in Python or other backend languages. Strong fundamentals in system design, performance, and debugging. • Experience with data systems and data modeling (databases, pipelines, etc.). • Real-world experience running experiments, measuring outcomes, and iterating. Bonus points • Advanced degree or research experience. • Good understanding of modern, AI-driven software development. Why Tenzai • Working on problems that matter - Software is now written and deployed faster than it can be secured. Attackers are beginning to use AI to find vulnerabilities at scale. Tenzai exists to close that gap. It's a mission that requires elite hackers, and also sharp storytellers, wicked-smart operators, and experienced market builders. • Building a category in the making - Tenzai is defining a new category in cybersecurity. That means every team — from research and engineering to product, brand, and go-to-market — has a chance to shape how the industry understands and adopts autonomous security. If you thrive building something from zero and helping a new idea take hold in the world, keep reading. • Talent density - We believe small teams of exceptional people outperform large organizations. Tenzai was founded by veteran security experts and repeat entrepreneurs. We hire deliberately and value curiosity, initiative, and craftsmanship, whatever your discipline. • Creating real impact, quickly - Whether you're building systems, shaping product experiences, telling the story, or helping customers succeed, your work will immediately influence how organizations secure their software. We move quickly, keep teams lean, and give humans ownership. • Ambition with humility - We're tackling hard problems with a team that values deep expertise and thoughtful collaboration. Everyone here is learning, experimenting, and pushing the boundaries of what's possible. Plus, we love eating lunch together.

Description About Cyera Come join the company building the security operating model for the age of AI. AI has changed how data is used - and security must change with it. Cyera's mission is to empower businesses to accelerate AI Adoption by defining a holistic approach to securing AI - from data to access to model. Instead of perimeter controls and static policies, Cyera provides a unified control plane that understands relationships between data, access, and behaviors across humans, systems, and AI. Backed by the world's leading investors and working with a large and growing list of Fortune 1000 companies, we are looking for world-class talent to join us as we usher in the new era of data and AI security. About the Team The ML Engineering team designs and builds the infrastructure and platforms that enable researchers and engineers to develop, evaluate, deploy, and operate ML models and LLM-based features at scale. We own the systems behind the ML lifecycle - from GPU-based training and evaluation workflows to model serving, LLM infrastructure, observability, internal SDKs, and developer tooling. Our internal platforms are used across multiple teams at Cyera, while the production services we enable power ML capabilities used across our customer base. We work closely with research, engineering, and DevOps teams, taking solutions from early ideation and design through experimentation and into reliable production systems. We value technical depth, ownership, curiosity, and a holistic approach to solving problems. About the Role We're looking for a strong and curious ML Engineer to join our team and help design, build, and operate the infrastructure behind our machine learning and LLM systems. In this role, you'll work across different parts of the ML lifecycle, from building evaluation workflows and improving CI/CD processes to operating production ML services and evolving our LLM infrastructure. You'll work closely with researchers, data scientists, backend engineers, and DevOps engineers to build infrastructure that enables ML solutions to move efficiently from research and experimentation to production. We're looking for someone with a holistic engineering mindset who enjoys understanding problems end-to-end - the business need, ML requirements, surrounding systems, and production environment - and turning them into reliable technical solutions. What You'll Do • Design and build ML workflows for model training, large-scale evaluation, batch prediction, and experimentation, enabling researchers and data scientists to iterate efficiently and reliably. • Develop ML infrastructure and developer tooling by automating recurring processes, improving CI/CD and model build flows, and creating tools that simplify ML development and operations. • Operate and improve production ML services, strengthening monitoring, observability, reliability, and performance across our ML and LLM systems. • Deploy and operate ML workloads on Kubernetes and cloud infrastructure, including GPU-based training, evaluation, and inference workloads. • Contribute to our LLM platform, including self-hosted model serving, LLM gateways, internal SDKs, evaluation and observability infrastructure, and integrations with different model providers. • Own engineering problems end-to-end, from ideation and understanding business and technical requirements through system design, implementation, deployment, and production operation. • Collaborate across research and engineering teams to build scalable infrastructure that enables ML solutions to move from experimentation into production. • Explore, evaluate, and integrate emerging technologies across ML infrastructure, LLMs, and agentic systems to continuously improve our platform and workflows. Requirements Who You Are • You have 4+ years of experience in ML engineering, software engineering, backend engineering, or a similar hands-on engineering role. • You have a B.Sc. in Computer Science, Software Engineering, or a related technical field, or equivalent significant practical experience. • You have strong Python and software engineering skills, with experience designing and building maintainable, production-quality systems. • You have hands-on experience with Kubernetes and Docker, including deploying, debugging, and operating production workloads. • You have strong experience with cloud environments such as AWS, GCP, or Azure and understand the infrastructure around running distributed production services. • You have experience with ML infrastructure and the ML lifecycle, including areas such as orchestration, model serving, evaluation, training, or production inference. • You have experience with CI/CD, observability, and production operations, and understand what it takes to make services reliable beyond simply deploying them. • You excel at solving complex problems end-to-end, independently understanding the business context, requirements, and surrounding systems and driving solutions from design through production. • You collaborate effectively across research and engineering disciplines and can communicate technical decisions clearly. • You are technically curious and proactive, with the ability to dive into unfamiliar technologies and understand how systems work under the hood. Nice-to-Haves • You have experience with GPU workloads or high-scale ML inference, including technologies such as vLLM, BentoML, Argo Workflows, Kubeflow, or similar. • You have experience with LLM platforms and infrastructure, such as LLM gateways, evaluation/observability tooling, self-hosted models, or internal LLM SDKs. • You have experience with agentic systems, including building agents, memory layers, agent evaluation, or related infrastructure. Why Join Us? At Cyera, we own what we build and how we work. Cyerans are empowered to take initiative, move quickly, and turn ideas into impact. We push boundaries by challenging the status quo, learning fast, and continuously raising the bar - for ourselves and for the industry. We elevate together by lifting each other up, celebrating wins as a team, and recognizing that our success is shared. Feel free to apply even if your experience doesn't tick every box. We're building something special here---and we welcome Cyerans with diverse backgrounds, perspectives, and experiences

Machine Learning Engineer About Millennium Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors. Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact. Our Israel office is located in the Bursa area of Ramat Gan. This role is on-site. As a global firm, proficiency in English is required. Meet the Team The Information Technology department is core to the health and growth of Millennium’s business. Supporting the firm’s active, multi-manager model, the team develops flexible, scalable technology and advanced proprietary systems, including next-generation analytical, trading, and AI capabilities. Based on-site in Millennium’s Israel office in the Bursa area of Ramat Gan, the team builds and evolves enterprise technology platforms that enable innovation across the firm. What You'll Do • Lead the development of AI and machine learning capabilities within the infrastructure group across multiple applications. • Transform rapid prototypes into production-grade AI and machine learning systems that deliver measurable business value. • Identify repeatable patterns and technical friction points across Millennium’s AI stack, translating them into reusable capabilities such as LLM routing and dedicated-hardware inference optimization. • Design and implement scalable AI infrastructure that supports federated agent development and distributed deployment across the organization. • Orchestrate AI agents across distributed systems and service buses, ensuring generated code aligns with enterprise architecture standards and best practices. • Build high-performance evaluation pipelines and observability frameworks to assess agentic systems against rigorous accuracy, safety, and latency requirements. • Advance the adoption of AI-augmented development practices by providing technical leadership and integrating AI-powered tools into engineering workflows and CI/CD pipelines. • Partner directly with teams across the firm to teach AI infrastructure best practices and guide successful adoption. What You Bring • Bachelor’s degree with 6+ years of experience, Master’s degree with 4+ years of experience, or PhD with 2+ years of experience in Computer Science, Data Science, Machine Learning, or a related field. • Experience building or operating AI/ML infrastructure, agent orchestration platforms, or comparable AI-powered development tools. • Proficiency in Python and PyTorch or a similar deep learning framework. • Strong understanding of enterprise software architecture patterns and distributed systems design. • Production experience with Docker, Kubernetes, and container orchestration. • Strong communication and teaching skills, with the ability to partner effectively with teams across the organization as a deployed engineer. • Experience with cloud platforms such as AWS, Azure, or GCP; infrastructure-as-code tools; and MLOps practices, including model training, versioning, deployment, monitoring, drift detection, and performance optimization. • Experience building agentic AI systems using frameworks such as LangGraph, LangChain, or PydanticAI, including LLM integration, tool calling, structured outputs, MCP implementations, vector databases, embedding pipelines, and retrieval-augmented generation architectures.

Description Join Noma Security and help shape the future of AI security in a fast-paced, high-impact environment. Noma is building the first comprehensive AI Security and Governance Platform, helping organizations adopt AI and LLMs with confidence and control. As AI becomes core to modern enterprises, we provide seamless visibility and protection across the entire AI lifecycle. Our team works at the intersection of AI, security, and cloud, shaping a new category in a rapidly evolving market. At Noma, you’ll have the opportunity to make a meaningful impact while working with exceptional people on technology that truly matters. We’re looking for a Senior MLOps Engineer to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights. As we scale our AIDR product and expand deeper into model-driven security intelligence, we are looking for a Senior MLOps Engineer to own the infrastructure, tooling, and operational foundations that power our NLP and LLM training, evaluation, and deployment workflows. You will architect and operate the systems that enable us to train, fine-tune, deploy, and monitor models at scale making ML at Noma reliable, fast, cost-efficient, and production-ready. This is a high-visibility, high-impact role where you will partner closely with DevOps, Backend, Data, and Product to establish world-class ML infrastructure from the ground up. 🛠️ What You’ll Do • Build & Scale ML Pipelines • Design, build, and maintain pipelines for training, fine-tuning, evaluating, and deploying NLP and LLM models across GPU and CPU environments. • Establish LLM-Focused CI/CD • Implement automated CI/CD workflows for ML models, including benchmarking, testing, performance gating, and production deployment. • Optimize Runtime & Inference • Select and optimize serving frameworks for low-latency, high-throughput inference, ensuring reliability and scalability. • Own ML Infrastructure • Manage training environments, experiment tracking, model registries, artifact versioning, and distributed training systems. • Operational Excellence • Monitor and optimize production models for performance, cost efficiency, availability, and observability. ✅ Requirement for success: • 5+ years in software engineering, MLOps, or ML engineering with hands-on experience deploying ML models to production. • Strong Python fundamentals and deep understanding of transformer architectures, tokenization, and NLP frameworks (PyTorch, HuggingFace). • Proven experience deploying and scaling LLMs for real-time inference—ideally on platforms like SageMaker, Vertex AI, or similar. • Expertise in GPU optimization, distributed training, and CPU-based inference optimization. • Strong cloud and Kubernetes background (EKS/GKE/AKS, Helm, Terraform, CI/CD for ML). 🎯 Nice to Haves • Background in building or operating internal ML platforms. • Knowledge of evaluation frameworks for LLM quality, robustness, or observability. • Experience working with data-driven ML operations, cost optimization, and model observability. • Understanding of security implications in ML pipelines. • Familiarity with multi-model orchestration, vector DBs, or retrieval pipelines. 💙 Perks & Benefits • Located in a prime area with easy access to public transportation, near the Hashalom train station and the Light Rail. • A bright, spacious, dog-friendly office that makes you smile the moment you walk in 🐶 • Team bonding activities, company retreats, happy hours, and holiday gifts • Pilates classes at the office 💪🧘‍♀️ • Never hungry: Monthly lunch budget, dinners provided, and a fully stocked kitchen 🍽️ • A warm, supportive, and people-first company culture • Pension & Keren Hishtalmut (advanced training fund) • A global work environment with teams across Tel Aviv, the US, the Netherlands, and London • Options that let you share in Noma’s growth and success